The impact of physical fitness, social life, and cognitive functions on work ability in middle-aged and older adults

Abstract

Objective: Demographic changes encompass societies to maintain the work ability (WA) of aging workforces. The present study explored the relationship between modifiable lifestyle factors, cognitive functions, and their influence on WA, using a multi-group structural equation approach.

Method: Cross-sectional data from 247 middle-aged and 236 older employees from the Dortmund Vital Study were included in this analysis. We proposed a model with three exogenous variables (Physical Fitness, Cognitive Functions, and Social Life), and with WA as the endogenous variable. WA was measured with the Work Ability Index (WAI), which considers job demands and individual physical and mental resources. Multi-group analyses were based on the principles of invariance testing and conducted using robust estimation methods.

Results: Results revealed that Social Life outside work had significant positive effects on WA in both, middle-aged and older adults. Physical Fitness had a significant effect on WA only in middle-aged adult, and Cognitive Functions had no significant influence on WA in either group. In older adults, Physical Fitness correlated with Cognitive Functions, whereas in middle-aged adults, Cognitive Functions marginally correlated with Social Life.

Conclusions: Our results underline the importance of an active social life outside the workplace for WA, regardless of the employees' age. The influence of Physical Fitness on WA changes with increasing age, indicating the necessity to have a differentiated view of age effects and interacting influencing factors. Our research contributes to the knowledge of how WA could be most effectively promoted in different age groups.

Clinicaltrials: gov NCT05155397; https://clinicaltrials.gov/ct2/show/NCT05155397 .

Keywords: Aging; Lifestyle factors, cognition, structural equation model (SEM); Occupational health; Work ability index.

Fig. 1

Hypothesized model. One-headed lines represent unstandardized regression coefficients, and two-headed curved lines represent correlations. O older adults, M middle-aged adults, Social social life, CF cognitive functions, WAI work ability index

Fig. 2

Network of associations based on polychoric, polyserial, and Pearson’s correlations for (a) middle-aged, and (b) older adults. Each node represents one of the indicator variables and the edges represent the strength of the correlations between the variables. Green edges represent positive correlations and red edges represent negative correlations. The width and color of the edges correspond to the absolute value of the correlations. Nodes are placed according to a forced-embedded algorithm (Fruchterman and Reingold 1991) in which the length of edges depends on the absolute weight of the edges. d2  d2-R Test of attentional endurance, DS  Digit-Span Backward, DST  Digit Substitution Test, FrF  frequency of social contacts, FrN  number of friends, LPS3  logical reasoning, LPS7  spatial rotation, LPA  lüdenscheid physical activity Questionnaire, Str  stroop test, Pmx  maximum power output in watt of the physical work capacity test; PWR  power-to-weight ratio of the physical work capacity test, QLs  WHOQoL social dimension, WAI  work ability index

Fig. 3

Path diagram for (a) middle-aged, and (b) older adults. Social, CF, and Fitness constitute the independent (exogenous) factors, and WAI, the dependent (endogenous factor). One-headed lines represent unstandardized regression coefficients, and two-headed curved lines represent correlations. Social  social life, CF  cognitive functions, WAI work ability index. Observed variables are omitted. * < .05; ** < .01; *** < .001